This is an automated email from the ASF dual-hosted git repository.
github-bot pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/datafusion.git
The following commit(s) were added to refs/heads/main by this push:
new ce08307a4c refactor: Use `Signature::coercible` for isnan/iszero
(#19604)
ce08307a4c is described below
commit ce08307a4ce9c3f282eee5bdf6f7f03289b05d86
Author: Kumar Ujjawal <[email protected]>
AuthorDate: Wed Jan 7 12:50:29 2026 +0530
refactor: Use `Signature::coercible` for isnan/iszero (#19604)
## Which issue does this PR close?
<!--
We generally require a GitHub issue to be filed for all bug fixes and
enhancements and this helps us generate change logs for our releases.
You can link an issue to this PR using the GitHub syntax. For example
`Closes #123` indicates that this PR will close issue #123.
-->
- Part of #14763.
## Rationale for this change
<!--
Why are you proposing this change? If this is already explained clearly
in the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand
your changes and offer better suggestions for fixes.
-->
## What changes are included in this PR?
Replace `TypeSignature::Exact` patterns with cleaner APIs:
- `isnan/iszero`: `Signature::coercible` with
`TypeSignatureClass::Float`
- `nanvl`: `Signature::uniform(2, [Float32, Float64])`
<!--
There is no need to duplicate the description in the issue here but it
is sometimes worth providing a summary of the individual changes in this
PR.
-->
## Are these changes tested?
Yes
<!--
We typically require tests for all PRs in order to:
1. Prevent the code from being accidentally broken by subsequent changes
2. Serve as another way to document the expected behavior of the code
If tests are not included in your PR, please explain why (for example,
are they covered by existing tests)?
-->
## Are there any user-facing changes?
<!--
If there are user-facing changes then we may require documentation to be
updated before approving the PR.
-->
<!--
If there are any breaking changes to public APIs, please add the `api
change` label.
-->
---------
Co-authored-by: Jeffrey Vo <[email protected]>
---
datafusion/functions/src/math/iszero.rs | 32 ++++++++++++++++++++++----------
datafusion/functions/src/math/nans.rs | 32 +++++++++++++++++++++-----------
datafusion/functions/src/math/nanvl.rs | 27 ++++++++++++++++++++++-----
3 files changed, 65 insertions(+), 26 deletions(-)
diff --git a/datafusion/functions/src/math/iszero.rs
b/datafusion/functions/src/math/iszero.rs
index 6349551ca0..ba4afc5622 100644
--- a/datafusion/functions/src/math/iszero.rs
+++ b/datafusion/functions/src/math/iszero.rs
@@ -18,12 +18,13 @@
use std::any::Any;
use std::sync::Arc;
-use arrow::array::{ArrayRef, AsArray, BooleanArray};
-use arrow::datatypes::DataType::{Boolean, Float32, Float64};
-use arrow::datatypes::{DataType, Float32Type, Float64Type};
+use arrow::array::{ArrayRef, ArrowNativeTypeOp, AsArray, BooleanArray};
+use arrow::datatypes::DataType::{Boolean, Float16, Float32, Float64};
+use arrow::datatypes::{DataType, Float16Type, Float32Type, Float64Type};
-use datafusion_common::{Result, exec_err};
-use datafusion_expr::TypeSignature::Exact;
+use datafusion_common::types::NativeType;
+use datafusion_common::{Result, ScalarValue, exec_err};
+use datafusion_expr::{Coercion, TypeSignatureClass};
use datafusion_expr::{
ColumnarValue, Documentation, ScalarFunctionArgs, ScalarUDFImpl, Signature,
Volatility,
@@ -59,12 +60,14 @@ impl Default for IsZeroFunc {
impl IsZeroFunc {
pub fn new() -> Self {
- use DataType::*;
+ // Accept any numeric type and coerce to float
+ let float = Coercion::new_implicit(
+ TypeSignatureClass::Float,
+ vec![TypeSignatureClass::Numeric],
+ NativeType::Float64,
+ );
Self {
- signature: Signature::one_of(
- vec![Exact(vec![Float32]), Exact(vec![Float64])],
- Volatility::Immutable,
- ),
+ signature: Signature::coercible(vec![float],
Volatility::Immutable),
}
}
}
@@ -87,6 +90,10 @@ impl ScalarUDFImpl for IsZeroFunc {
}
fn invoke_with_args(&self, args: ScalarFunctionArgs) ->
Result<ColumnarValue> {
+ // Handle NULL input
+ if args.args[0].data_type().is_null() {
+ return Ok(ColumnarValue::Scalar(ScalarValue::Boolean(None)));
+ }
make_scalar_function(iszero, vec![])(&args.args)
}
@@ -108,6 +115,11 @@ fn iszero(args: &[ArrayRef]) -> Result<ArrayRef> {
|x| x == 0.0,
)) as ArrayRef),
+ Float16 => Ok(Arc::new(BooleanArray::from_unary(
+ args[0].as_primitive::<Float16Type>(),
+ |x| x.is_zero(),
+ )) as ArrayRef),
+
other => exec_err!("Unsupported data type {other:?} for function
iszero"),
}
}
diff --git a/datafusion/functions/src/math/nans.rs
b/datafusion/functions/src/math/nans.rs
index be21cfde0a..03f246c28b 100644
--- a/datafusion/functions/src/math/nans.rs
+++ b/datafusion/functions/src/math/nans.rs
@@ -17,9 +17,10 @@
//! Math function: `isnan()`.
-use arrow::datatypes::{DataType, Float32Type, Float64Type};
-use datafusion_common::{Result, exec_err};
-use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, TypeSignature};
+use arrow::datatypes::{DataType, Float16Type, Float32Type, Float64Type};
+use datafusion_common::types::NativeType;
+use datafusion_common::{Result, ScalarValue, exec_err};
+use datafusion_expr::{Coercion, ColumnarValue, ScalarFunctionArgs,
TypeSignatureClass};
use arrow::array::{ArrayRef, AsArray, BooleanArray};
use datafusion_expr::{Documentation, ScalarUDFImpl, Signature, Volatility};
@@ -54,15 +55,14 @@ impl Default for IsNanFunc {
impl IsNanFunc {
pub fn new() -> Self {
- use DataType::*;
+ // Accept any numeric type and coerce to float
+ let float = Coercion::new_implicit(
+ TypeSignatureClass::Float,
+ vec![TypeSignatureClass::Numeric],
+ NativeType::Float64,
+ );
Self {
- signature: Signature::one_of(
- vec![
- TypeSignature::Exact(vec![Float32]),
- TypeSignature::Exact(vec![Float64]),
- ],
- Volatility::Immutable,
- ),
+ signature: Signature::coercible(vec![float],
Volatility::Immutable),
}
}
}
@@ -84,6 +84,11 @@ impl ScalarUDFImpl for IsNanFunc {
}
fn invoke_with_args(&self, args: ScalarFunctionArgs) ->
Result<ColumnarValue> {
+ // Handle NULL input
+ if args.args[0].data_type().is_null() {
+ return Ok(ColumnarValue::Scalar(ScalarValue::Boolean(None)));
+ }
+
let args = ColumnarValue::values_to_arrays(&args.args)?;
let arr: ArrayRef = match args[0].data_type() {
@@ -96,6 +101,11 @@ impl ScalarUDFImpl for IsNanFunc {
args[0].as_primitive::<Float32Type>(),
f32::is_nan,
)) as ArrayRef,
+
+ DataType::Float16 => Arc::new(BooleanArray::from_unary(
+ args[0].as_primitive::<Float16Type>(),
+ |x| x.is_nan(),
+ )) as ArrayRef,
other => {
return exec_err!(
"Unsupported data type {other:?} for function {}",
diff --git a/datafusion/functions/src/math/nanvl.rs
b/datafusion/functions/src/math/nanvl.rs
index 345b1a5b71..6daf476e25 100644
--- a/datafusion/functions/src/math/nanvl.rs
+++ b/datafusion/functions/src/math/nanvl.rs
@@ -20,9 +20,9 @@ use std::sync::Arc;
use crate::utils::make_scalar_function;
-use arrow::array::{ArrayRef, AsArray, Float32Array, Float64Array};
-use arrow::datatypes::DataType::{Float32, Float64};
-use arrow::datatypes::{DataType, Float32Type, Float64Type};
+use arrow::array::{ArrayRef, AsArray, Float16Array, Float32Array,
Float64Array};
+use arrow::datatypes::DataType::{Float16, Float32, Float64};
+use arrow::datatypes::{DataType, Float16Type, Float32Type, Float64Type};
use datafusion_common::{DataFusionError, Result, exec_err};
use datafusion_expr::TypeSignature::Exact;
use datafusion_expr::{
@@ -66,10 +66,13 @@ impl Default for NanvlFunc {
impl NanvlFunc {
pub fn new() -> Self {
- use DataType::*;
Self {
signature: Signature::one_of(
- vec![Exact(vec![Float32, Float32]), Exact(vec![Float64,
Float64])],
+ vec![
+ Exact(vec![Float16, Float16]),
+ Exact(vec![Float32, Float32]),
+ Exact(vec![Float64, Float64]),
+ ],
Volatility::Immutable,
),
}
@@ -91,6 +94,7 @@ impl ScalarUDFImpl for NanvlFunc {
fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
match &arg_types[0] {
+ Float16 => Ok(Float16),
Float32 => Ok(Float32),
_ => Ok(Float64),
}
@@ -130,6 +134,19 @@ fn nanvl(args: &[ArrayRef]) -> Result<ArrayRef> {
.map(|res| Arc::new(res) as _)
.map_err(DataFusionError::from)
}
+ Float16 => {
+ let compute_nanvl =
+ |x: <Float16Type as
arrow::datatypes::ArrowPrimitiveType>::Native,
+ y: <Float16Type as
arrow::datatypes::ArrowPrimitiveType>::Native| {
+ if x.is_nan() { y } else { x }
+ };
+
+ let x = args[0].as_primitive() as &Float16Array;
+ let y = args[1].as_primitive() as &Float16Array;
+ arrow::compute::binary::<_, _, _, Float16Type>(x, y, compute_nanvl)
+ .map(|res| Arc::new(res) as _)
+ .map_err(DataFusionError::from)
+ }
other => exec_err!("Unsupported data type {other:?} for function
nanvl"),
}
}
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
